Quick Guide to IBM® SPSS®: Statistical Analysis With Step-by-Step Examples gives students the extra guidance with SPSS they need without taking up valuable in-class time. A practical, accessible guide for using software while doing data analysis in the social sciences, students can learn SPSS on their own, allowing instructors to focus on the concepts and calculations in their lectures, rather than SPSS tutorials. Designed to work across disciplines, the authors have provided a number of SPSS "step-by-step" examples in chapters showing the user how to plan a study, prepare data for analysis, perform the analysis and interpret the output from SPSS.

The new Third Edition covers IBM® SPSS® version 25, includes a new section on Syntax, and all chapters have been updated to reflect current menu options along with many SPSS screenshots, making the process much simpler for the user. In addition, helpful hints and insights are provided through the features "Tips and Caveats" and "Sidebars."

Preface & Acknowledgments

About the Authors

Chapter 1 • Introduction

Getting the Most Out of Quick Guide to IBM SPSS

A Brief Overview of the Statistical Process

Understanding Hypothesis Testing, Power, and Sample Size

Understanding the p-Value

Planning a Successful Analysis

Guidelines for Creating Data Sets

Preparing Excel Data for Import

Guidelines for Reporting Results

Downloading Sample SPSS Data Files

Opening Data Files for Examples

Summary

References

Chapter 2 • Describing and Examining Data

Example Data Files

Describing Quantitative Data

Describing Categorical Data

Summary

References

Chapter 3 • Creating and Using Graphs

Introduction to SPSS Graphs

Guidelines for Creating and Using Graphs

Chart Builder

Graphboard Template Chooser

Legacy Plots

Scatterplots

Histograms

Bar Charts

Pie Charts

Boxplots

Summary

References

Chapter 4 • Comparing One or Two Means Using the t-Test

One-Sample t-Test

Two-Sample t-Test

Paired t-Test

Summary

References

Chapter 5 • Correlation and Regression

Correlation Analysis

Simple Linear Regression

Multiple Linear Regression

Summary

References

Chapter 6 • Analysis of Categorical Data

Contingency Table Analysis (r × c)

Contingency Table Examples

McNemar’s Test

Mantel-Haenszel Meta-Analysis Comparison

Tests of Interrater Reliability

Goodness-of-Fit Test

Other Measures of Association for Categorical Data

Summary

References

Chapter 7 • Analysis of Variance and Covariance

One-Way ANOVA

Two-Way Analysis of Variance

Repeated-Measures Analysis of Variance

Analysis of Covariance

Summary

References

Chapter 8 • Nonparametric Analysis Procedures

Spearman’s Rho

Mann-Whitney-Wilcoxon (Two Independent Groups Test)

Kruskal-Wallis Test

Sign Test and Wilcoxon Signed-Rank Test for Matched Pairs

Friedman’s Test

Summary

Reference

Chapter 9 • Logistic Regression

Appropriate Applications for Logistic Regression

Simple Logistic Regression

Multiple Logistic Regression

Summary

References

Appendix A: A Brief Tutorial for Using IBM SPSS for Windows

Appendix B: Choosing the Right Procedure to Use

Index

“Wonderful feedback from my graduate students using this textbook!”

Shlomo Sawilowsky

Wayne State University

“This book is an ideal resource and a guide for understanding basic concepts of statistics.”

Vinayak Nahar

Lincoln Memorial University

“I really appreciate the detailed yet also practical approach. I also appreciate the comprehensive approach to the topics so that students are better grounded in how to think about their statistical analysis.”